teal module: Principal component analysis

Usage

tm_a_pca(
  label = "Principal Component Analysis",
  dat,
  plot_height = c(600, 200, 2000),
  plot_width = NULL,
  ggtheme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"),
  ggplot2_args = teal.widgets::ggplot2_args(),
  rotate_xaxis_labels = FALSE,
  font_size = c(12, 8, 20),
  alpha = c(1, 0, 1),
  size = c(2, 1, 8),
  pre_output = NULL,
  post_output = NULL
)

Arguments

label

(character(1)) Label shown in the navigation item for the module or module group. For modules() defaults to "root". See Details.

dat

(data_extract_spec or list of multiple data_extract_spec) specifying columns used to compute PCA.

plot_height

(numeric) optional, specifies the plot height as a three-element vector of value, min, and max intended for use with a slider UI element.

plot_width

(numeric) optional, specifies the plot width as a three-element vector of value, min, and max for a slider encoding the plot width.

ggtheme

(character) optional, ggplot2 theme to be used by default. Defaults to "gray".

ggplot2_args

(ggplot2_args) optional, object created by teal.widgets::ggplot2_args() with settings for all the plots or named list of ggplot2_args objects for plot-specific settings. The argument is merged with options variable teal.ggplot2_args and default module setup.

List names should match the following: c("default", "Elbow plot", "Circle plot", "Biplot", "Eigenvector plot").

For more details see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets").

rotate_xaxis_labels

(logical) optional, whether to rotate plot X axis labels. Does not rotate by default (FALSE).

font_size

(numeric) optional, specifies font size. It controls the font size for plot titles, axis labels, and legends.

• If vector of length == 1 then the font sizes will have a fixed size.

• while vector of value, min, and max allows dynamic adjustment.

alpha

(integer(1) or integer(3)) optional, specifies point opacity.

• When the length of alpha is one: the plot points will have a fixed opacity.

• When the length of alpha is three: the plot points opacity are dynamically adjusted based on vector of value, min, and max.

size

(integer(1) or integer(3)) optional, specifies point size.

• When the length of size is one: the plot point sizes will have a fixed size.

• When the length of size is three: the plot points size are dynamically adjusted based on vector of value, min, and max.

pre_output

(shiny.tag) optional, text or UI element to be displayed before the module's output, providing context or a title. with text placed before the output to put the output into context. For example a title.

post_output

(shiny.tag) optional, text or UI element to be displayed after the module's output, adding context or further instructions. Elements like shiny::helpText() are useful.

Value

Object of class teal_module to be used in teal applications.

Examples

library(teal.widgets)

# general data example
data <- teal_data()
data <- within(data, {
  require(nestcolor)
  USArrests <- USArrests
})

datanames(data) <- "USArrests"

app <- init(
  data = data,
  modules = modules(
    tm_a_pca(
      "PCA",
      dat = data_extract_spec(
        dataname = "USArrests",
        select = select_spec(
          choices = variable_choices(
            data = data[["USArrests"]], c("Murder", "Assault", "UrbanPop", "Rape")
          ),
          selected = c("Murder", "Assault"),
          multiple = TRUE
        ),
        filter = NULL
      ),
      ggplot2_args = ggplot2_args(
        labs = list(subtitle = "Plot generated by PCA Module")
      )
    )
  )
)
#> [INFO] 2024-03-05 18:46:02.7099 pid:1279 token:[] teal.modules.general Initializing tm_a_pca
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# CDISC data example
data <- teal_data()
data <- within(data, {
  require(nestcolor)
  ADSL <- rADSL
})
datanames(data) <- "ADSL"
join_keys(data) <- default_cdisc_join_keys[datanames(data)]

app <- init(
  data = data,
  modules = modules(
    tm_a_pca(
      "PCA",
      dat = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          choices = variable_choices(
            data = data[["ADSL"]], c("BMRKR1", "AGE", "EOSDY")
          ),
          selected = c("BMRKR1", "AGE"),
          multiple = TRUE
        ),
        filter = NULL
      ),
      ggplot2_args = ggplot2_args(
        labs = list(subtitle = "Plot generated by PCA Module")
      )
    )
  )
)
#> [INFO] 2024-03-05 18:46:02.8401 pid:1279 token:[] teal.modules.general Initializing tm_a_pca
if (interactive()) {
  shinyApp(app$ui, app$server)
}